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Please use this identifier to cite or link to this item: http://hdl.handle.net/2328/26267

Title: Discovering itemset interactions
Authors: Liang, Ping
Roddick, John Francis
Ceglar, Aaron John
Shillabeer, Anna
de Vries, Denise Bernadette
Keywords: Computing
Data mining
Itemset interaction
Relative support
Issue Date: 2009
Publisher: Australian Computer Society
Citation: Liang, P., Roddick, J.F., Ceglar, A.J., Shillabeer, A. and de Vries, D.B., 2009. Discovering itemset interactions. ACSC '09: Proceedings of the Thirty-Second Australasian Conference on Computer Science, vol. 91, 133-140.
Abstract: Itemsets, which are treated as intermediate results in association mining, have attracted significant research due to the inherent complexity of their generation. However, there is currently little literature focusing upon the interactions between itemsets, the nature of which may potentially contain valuable information. This paper presents a novel tree-based approach to discovering item-set interactions, a task which cannot be undertaken by current association mining techniques.
URI: http://hdl.handle.net/2328/26267
Appears in Collections:Computer Science, Engineering and Mathematics - Collected Works

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